Staff AI Engineer
HartleyCoAbout the role
I’m supporting one of the fastest-growing applied AI companies in San Francisco as they hire a Staff AI Engineer for their Agent Team.
The company is building production AI agents for the insurance industry, replacing complex manual workflows across carriers, brokers and enterprise businesses.
They have:
Raised more than $30M from a16z, Y Combinator, Nexus and South Park Commons
Grown rapidly over the past 12 months
Signed top-10 insurance carriers and brokers
Deployed with Fortune 100 and public companies
Built a deeply technical team with experience from Apple AI Research, Brex, Coinbase, Uber and multiple YC startups
This is not a model-training or research role.
You’ll be building the systems above the foundation models that make agents reliable in production.
What You’ll Own
End-to-end evaluation systems for agent performance
Agent orchestration across long-running workflows
Tools and MCP servers connecting agents to enterprise systems
Context, memory and reasoning strategies
Multi-agent systems and feedback-driven improvement loops
Production reliability, observability and failure recovery
Experiments that turn emerging AI research into product capabilities
Both founders are engineers, and engineers have a genuine say in product direction.
This is a hands-on Staff role for someone who wants to set technical direction, make meaningful architecture decisions and help define how a category-leading company builds agents.
The Ideal Background
8+ years of software engineering experience
3+ years building in AI or machine learning
Strong Python and backend engineering fundamentals
Recent experience shipping production LLM or agent systems
Ownership of architecture beyond individual features
Experience with evals, orchestration, tool use, context engineering or agent reliability
Strong communication and product judgement
Comfortable working at speed in an ambitious, on-site environment
Previous startup, early engineering or founder experience would be particularly valuable.
Insurance experience is not required.
Location: San Francisco, five days per week on-site
Compensation: $300K-$400K base + meaningful equity
Message me directly if you have built production agent systems and want to help define the technical foundations of a company with serious commercial momentum.
Responsibilities
- End-to-end evaluation systems for agent performance
- Agent orchestration across long-running workflows
- Tools and MCP servers connecting agents to enterprise systems
- Context, memory and reasoning strategies
- Multi-agent systems and feedback-driven improvement loops
- Production reliability, observability and failure recovery
- Experiments that turn emerging AI research into product capabilities
Qualifications
- 8+ years of software engineering experience
- 3+ years building in AI or machine learning
- Strong Python and backend engineering fundamentals
- Recent experience shipping production LLM or agent systems
- Ownership of architecture beyond individual features
- Experience with evals, orchestration, tool use, context engineering or agent reliability
- Strong communication and product judgement
- Comfortable working at speed in an ambitious, on-site environment
Benefits
- Meaningful equity
Skills mentioned
About HartleyCo
Founded in 2019, HartleyCo is a boutique Technology and Finance Search Firm. Across the UK, US and Central Europe, we deliver Permanent and Interim Recruitment Solutions, Consulting Services and Executive Search. Our expert teams focus on: Technology • Generative AI and LLM • Software Engineering • GTM People • C Suite inc Chief of Staff & CTO • Co-founder Our clients include a diverse range of businesses, from innovative start-ups at the very beginning of their journey, to some of the world’s largest corporations. With a dedicated focus on the VC & Private Equity markets, we have a deep understanding of the unique dynamics involved in working with VC/PE firms and scaling their Portco's. Simply put, HartleyCo are trusted advisors who provide fantastic recruitment experiences. We’re not trying to reinvent the wheel. We listen, advise then action.